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      Phylogenetic and environmental diversity of DsrAB-type dissimilatory (bi)sulfite reductases


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          The energy metabolism of essential microbial guilds in the biogeochemical sulfur cycle is based on a DsrAB-type dissimilatory (bi)sulfite reductase that either catalyzes the reduction of sulfite to sulfide during anaerobic respiration of sulfate, sulfite and organosulfonates, or acts in reverse during sulfur oxidation. Common use of dsrAB as a functional marker showed that dsrAB richness in many environments is dominated by novel sequence variants and collectively represents an extensive, largely uncharted sequence assemblage. Here, we established a comprehensive, manually curated dsrAB/DsrAB database and used it to categorize the known dsrAB diversity, reanalyze the evolutionary history of dsrAB and evaluate the coverage of published dsrAB-targeted primers. Based on a DsrAB consensus phylogeny, we introduce an operational classification system for environmental dsrAB sequences that integrates established taxonomic groups with operational taxonomic units (OTUs) at multiple phylogenetic levels, ranging from DsrAB enzyme families that reflect reductive or oxidative DsrAB types of bacterial or archaeal origin, superclusters, uncultured family-level lineages to species-level OTUs. Environmental dsrAB sequences constituted at least 13 stable family-level lineages without any cultivated representatives, suggesting that major taxa of sulfite/sulfate-reducing microorganisms have not yet been identified. Three of these uncultured lineages occur mainly in marine environments, while specific habitat preferences are not evident for members of the other 10 uncultured lineages. In summary, our publically available dsrAB/DsrAB database, the phylogenetic framework, the multilevel classification system and a set of recommended primers provide a necessary foundation for large-scale dsrAB ecology studies with next-generation sequencing methods.

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          BLAST+: architecture and applications

          Background Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. Results We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. Conclusion The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.
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            Codon-substitution models for heterogeneous selection pressure at amino acid sites.

            Comparison of relative fixation rates of synonymous (silent) and nonsynonymous (amino acid-altering) mutations provides a means for understanding the mechanisms of molecular sequence evolution. The nonsynonymous/synonymous rate ratio (omega = d(N)d(S)) is an important indicator of selective pressure at the protein level, with omega = 1 meaning neutral mutations, omega 1 diversifying positive selection. Amino acid sites in a protein are expected to be under different selective pressures and have different underlying omega ratios. We develop models that account for heterogeneous omega ratios among amino acid sites and apply them to phylogenetic analyses of protein-coding DNA sequences. These models are useful for testing for adaptive molecular evolution and identifying amino acid sites under diversifying selection. Ten data sets of genes from nuclear, mitochondrial, and viral genomes are analyzed to estimate the distributions of omega among sites. In all data sets analyzed, the selective pressure indicated by the omega ratio is found to be highly heterogeneous among sites. Previously unsuspected Darwinian selection is detected in several genes in which the average omega ratio across sites is 1. Genes undergoing positive selection include the beta-globin gene from vertebrates, mitochondrial protein-coding genes from hominoids, the hemagglutinin (HA) gene from human influenza virus A, and HIV-1 env, vif, and pol genes. Tests for the presence of positively selected sites and their subsequent identification appear quite robust to the specific distributional form assumed for omega and can be achieved using any of several models we implement. However, we encountered difficulties in estimating the precise distribution of omega among sites from real data sets.
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              The ecology and biotechnology of sulphate-reducing bacteria.

              Sulphate-reducing bacteria (SRB) are anaerobic microorganisms that use sulphate as a terminal electron acceptor in, for example, the degradation of organic compounds. They are ubiquitous in anoxic habitats, where they have an important role in both the sulphur and carbon cycles. SRB can cause a serious problem for industries, such as the offshore oil industry, because of the production of sulphide, which is highly reactive, corrosive and toxic. However, these organisms can also be beneficial by removing sulphate and heavy metals from waste streams. Although SRB have been studied for more than a century, it is only with the recent emergence of new molecular biological and genomic techniques that we have begun to obtain detailed information on their way of life.

                Author and article information

                ISME J
                ISME J
                The ISME Journal
                Nature Publishing Group
                May 2015
                24 October 2014
                1 May 2015
                : 9
                : 5
                : 1152-1165
                [1 ]Department of Microbiology and Ecosystem Science, Division of Microbial Ecology, Faculty of Life Sciences, University of Vienna , Vienna, Austria
                [2 ]Austrian Polar Research Institute , Vienna, Austria
                [3 ]Center for Geomicrobiology, Department of Bioscience, Aarhus University , Aarhus, Denmark
                [4 ]Division of Computational Systems Biology, Department of Microbiology and Ecosystem Science, Faculty of Life Sciences, University of Vienna , Vienna, Austria
                [5 ]Department of Biology, University of Konstanz , Konstanz, Germany
                Author notes
                [* ]Department of Microbiology and Ecosystem Science, Division of Microbial Ecology, Faculty of Life Sciences, University of Vienna , Althanstrasse 14, Wien 1090, Austria. E-mail: loy@ 123456microbial-ecology.net
                Copyright © 2015 International Society for Microbial Ecology

                This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/

                : 30 June 2014
                : 13 September 2014
                : 23 September 2014
                Original Article

                Microbiology & Virology
                Microbiology & Virology


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